CN105842689B - A kind of high resolution radar fast imaging method based on generalized reflection rate model - Google Patents
A kind of high resolution radar fast imaging method based on generalized reflection rate model Download PDFInfo
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Abstract
The invention discloses a kind of high resolution radar fast imaging method based on generalized reflection rate model.The present invention extends the Born approximation model of existing radar imagery, adds the anisotropic properties of the target characteristic different to the action effect of different frequency range signal from target in a model；The model is more nearly with actual signal model, enhances radar imagery effect, to realize that high resolution radar imaging has established model basis；And propose and radar imaging system is divided into sub-aperture or sub-band progress approximate calculation using three kinds of sparse characteristics of target generalized reflection rate；It is proposed that imaging region is divided into a series of sub- imaging regions according to system function characteristic, greatly accelerated image taking speed；It is further proposed that traditional radar imagery problem is converted into the image processing problem based on physical mechanism using dualistic transformation；The present invention not only ensure that radar imagery precision but also accelerate radar imagery speed, efficiently solve the technical barrier that can not carry out large scale high resolution radar real time imagery.
Description
Technical field
The present invention relates to radar imaging technology, and in particular to a kind of high resolution radar based on generalized reflection rate model is quick
Imaging method.
Background technology
With the rapid development of economic society, radar imaging system be nowadays widely used in geographical science, medical science and
Other various military and civilian scenes.Because radar imaging system is using frequency electromagnetic waves, it has stronger nonmetallic
Penetration capacity, it is possible to achieve effective detection to vanishing target.Such as：At night, for enemy military base carry out remote sensing into
Picture, the military operation of enemy army can be seen clearly in time；During counterterrorism operations and hostage's rescue, noncooperative target after wall is carried out
High-resolution imaging, strong reference can be provided to formulate rescue method；It is quick harmless in the public place such as airport and railway station
Ground carries out security sweep to hand baggage, it can be ensured that the life of the people is not encroached on property safety.
Radar imagery model is more using blast meta-model and Born approximation model at present, and both models are to a certain extent
It all have ignored the amplitude fading of echo-signal, the anisotropic properties of imageable target, different frequency range electromagnetic wave and imageable target
Action effect is different, and the Multiple Scattering effect between target.As the above analysis, current radar imagery model and reality
There is relatively large deviation in border imaging system, thus be provided with the obstacle that can not go beyond for the realization of high resolution radar imaging.Raising is built
Mould precision is to realize the fundamental way of high resolution radar imaging.
Radar imagery process is typical electromagnetism inverse problem, and its pathosis and high computation complexity are always scientific research
Focus.The method for solving electromagnetism inverse problem at present mainly has two classes：1st, offset method：Offset method is to be based on blast meta-model,
It assumes that target is made up of a series of isolated points, is typically realized using back-projection algorithm or time reversal algorithm.Its allusion quotation
Type algorithm such as range Doppler.Offset method is confined to narrow-band and the far field imaging system of small angle.2nd, chromatography method：It is based on
Born approximation model, it assumes that target is weak scattering material.Although the imaging precision of chromatography method is higher than offset method, layer
The computation complexity of analysis method will be far above offset method.
To sum up analysis is understood：Above two method for solving exists computationally intensive, is only applicable to compared with low-frequency range and smaller mesh
The shortcomings that dimensioning, in face of large scale high-resolution imaging problem, then two methods are helpless.Radar imagery process at present
Due to being limited to the excessively simple imaging model of above two, cause the presence of a large amount of ghosts in imaging results, it is post processing
During target recognition and classification bring serious burden.
Therefore, how under the conditions of existing radar hardware system, propose the radar imagery model of more high precision and improve thunder
Up to imaging efficiency, it is the great challenge that those skilled in the art are badly in need of solving to realize large scale high resolution radar real time imagery
The key technology difficulty of property.
The content of the invention
In order to solve above-mentioned key technology difficulty, the present invention proposes a kind of high-resolution thunder based on generalized reflection rate model
Up to fast imaging method.
The high resolution radar fast imaging method based on generalized reflection rate model of the present invention, comprises the following steps：
1) radar imaging system is established, obtains radar scattering data：
Radar imaging system includes T emitter, and R receiver, the frequency number of transmission signal is F, and emitter is successively
To targeted imaging region transmission signal, and by whole receiver receives echo-signals, then after t-th of emitter transmission signal,
The echo-signal received at each receiver is followed successively by yF,t=[yF,t,1；уF,t,2；…уF,t,R], wherein, T and R are respectively
>=2 natural number, t=1,2 ..., T, F are >=2 natural number；
2) generalized reflection rate model is established：
Generalized reflection rate model is built upon on the basis of traditional Born approximation model, and each to different comprising imageable target
Property characteristic and frequency characteristic, i.e., the reflectivity of imageable target is different under different angle emitter, and mesh is imaged under different operating frequency
The different characteristic of target reflectivity；
3) data conversion and Data Integration：
A) receiver receives frequency domain echo signal；
B) according to the Structural Characteristics of radar system function, according to generalized reflection rate model, radar imaging system is divided
For K sub-aperture or sub-band, and targeted imaging region is divided into B sub- imaging regions, according to above-mentioned division result, to frequency
Domain echo-signal is combined arrangement, obtains on b-th of sub- imaging region and the echo data of k-th of sub-aperture or sub-band
Function y(k,b), wherein, k=1,2 ..., K, b=1,2 ..., B, radar imagery system is constructed according to free space dyadic Green's function
Unite function A(k,b), then generalized reflection rate x(k,b)Meet equation (1)：
y(k,b)=A(k,b)x(k,b)+n(k,b) (1)
Wherein, n(k,b)Model error is represented, then radar imagery problem, which is converted into, solves unknown number x in equation (1)(k,b)'s
Inverse problem；
C) system function A is multiplied by respectively on equation (1) both sides(k,b)Associate matrixEquation (1) is entered
The pairing of lines converts to obtain equation (2)：
Wherein,It is the system function for representing image procossing,It is to represent
Rear orientation projection's imaging results, n(k,b)It is model error, traditional radar imagery problem is converted into based on thing by above-mentioned dualistic transformation
The radar image process problem of reason mechanism；
4) parallel imaging is carried out to sub- imaging region：
Based on generalized reflection rate model, each sub- imaging region is carried out simultaneously according to Gradient Iteration algorithm for equation (2)
Row is imaged, and the m times iteration of k-th of sub-aperture or sub-band under b-th of sub- imaging region obtains generalized reflection rateIt is full
Sufficient equation (3)：
Wherein,For k-th of the sub-aperture or the m of sub-band under b-th of sub- imaging region
The step factor of secondary iteration,For k-th of son under b-th of sub- imaging region
The gradient function of the m times iteration of aperture or sub-band；
Using generalized reflection rate model by the imaging results x of all K sub-apertures under b-th of sub- imaging region(k,b)Enter
Row image co-registration, obtain the imaging results x of b-th of sub- imaging region(b)：
Wherein, N represents x(k,b)Element number, n represents nth elements, and n=1,2 ..., N, p and q are norm indexes；
5) image co-registration：
By the imaging results x of B sub- imaging regions(b)Carry out image co-registration and can obtain a width complete object imaging region
High resolution radar imaging image X.
Wherein, in step 1), radar imaging system of the invention is applied to conventional various radar imaging systems；Radar
Each emitter of imaging system launches electromagnetic wave, all receivers while receives echo-signal successively.
In step 2), the original Born approximation model of generalized reflection rate model extension, and assume the different frequencies of different angle
The transmission signal of rate is different in induced-current caused by imageable target place.From electromagnetism integration method, receiver receives
Scattered field be represented by formula (5)：
E(rs；f,rt)=i ω μ0∫VDr ＇ G (rs, r ＇；F) J (r ＇, f；rt) (5)
Wherein, G (rs, r ＇；F) it is three-dimensional dyadic Green's function in free space, rtFor the position of emitter, rsTo connect
The position of receipts machine, r ＇ are the position of imageable target, and f is working frequency, and ω is angle working frequency, J (r ＇, f；rt) represent t-th
Emitter launches electromagnetic wave, in the induced-current changed caused by target r ＇ places with working frequency f, μ0It is the magnetic conductance in vacuum
Rate.According to generalized reflection rate model, formula (5) can be abbreviated as formula (6)：
y(f,t)=A(f,t)x(f,t)+n(f,t)F=1,2 ..., F, t=1,2 ..., T (6)
Wherein, F is frequency number, and T is emitter number.
The unknown number that direct solution formula (6) solves required for causing sharply increases, and makes imaging problem more complicated.This
Invention proposes to reduce unknown number using the method for dividing sub-aperture and sub-band using three kinds of sparse characteristics of imageable target
Number, so as to reduce imaging difficulty.Three kinds of sparse characteristics of imageable target include：
1st, as fixed generalized reflection rate x(f,t)Middle emitter t and frequency f, generalized reflection rate x(f,t)In certain transform domain
Must be sparse；
2nd, for one group of generalized reflection rate column vector { x(f,t), f=1,2 ..., F, t=1,2 ..., T } hair is described
Signal is penetrated in induced-current caused by target place, thus it has common physical basis, then generalized reflection rate { x(f,t)Tool
There is the architectural characteristic of joint sparse, this sparse characteristic can utilize (p, q) to mix norm (such as formula 4) to measure；
3rd, due to one group of generalized reflection rate x(f,t)The induced-current in imageable target is described, makes x(f,t)For row to
Amount, thus the matrix X of its horizontal meaders generation is low-rank matrix.
, can be by way of dividing sub-aperture and sub-band come solution formula (6) based on above-mentioned three kinds of sparse characteristics.Then
Formula (6) can be reduced to formula (7)：
y(k)=A(k)x(k)+n(k) (7)
Wherein, k=1,2 ..., K, K represent sub-aperture or the number of sub-band.
Step 3) a) in, if the echo-signal that receiver receives is time domain echo-signal, utilize quick Fu
In leaf transformation FFT time domain echo-signal is transformed to frequency domain echo signal.
In the b of step 3)) in, in order to realize Distributed Calculation, the present invention is tied using two kinds of image processing system function
Structure characteristic, two kinds of different sub- imaging region division methods are proposed respectively：
I. far-field effect method is ignored：Utilize the weaker spy of the correlation between two distant elements or action effect
Point, targeted imaging region is divided into the sub- imaging region of B imbricate, ignores the influence between distant element；
Ii. adjacent first constant method：It is approximately a constant using the interaction between two adjacent elements, by adjacent element
Reflectivity is set to identical value in same equation, i.e., original targeted imaging region is divided into B interlaced sons is imaged
Region, the large scale multivariate linear equations of solution are approximately a series of multiple linear equation of small yardsticks.
According to sub-aperture and the structure of sub- imaging region construction echo data function y(k,b)With radar imaging system function
A(k,b)。
Both members are same in formula (1) is multiplied by (A(k,b))*, so as to which traditional radar imagery problem is converted into based on physics
The image processing problem of mechanism.
In step 4), based on generalized reflection rate model, distribution is carried out to equation (2) according to Gradient Iteration algorithm and asked
Solution, the specific imaging process for carrying out parallel imaging to each sub- imaging region are as follows：
A) imaging results under each sub-aperture or sub-band are iterated to calculate：
I. iteration the m times, the gradient function of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is calculated
Ii. iteration the m times, the step factor of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is updated
Iii. iteration the m times, the generalized reflection rate of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is updated
Iv. judge whether to meet iterated conditional, such as meet, then into step b), be such as unsatisfactory for, then return to step i)；
B) by the imaging results x of the different sub-apertures of b-th of sub- imaging region(k,b)It is fused into piece image x(b)。
In step 5), according to the b of step 3) method of neutron imaging region division, the method for determining image co-registration；Such as
Fruit imaging region division methods are using far-field effect method is ignored, then image co-registration uses average weighted method；As fruit into
As region partitioning method uses adjacent first constant method, the then method that image co-registration uses interpolation.
Advantages of the present invention：
The present invention extends the Born approximation model of existing radar imagery, adds the anisotropic properties of target in a model
The characteristic different to the action effect of different frequency range signal from target, generalized reflection rate model is proposed first；The model and reality
Border signal model is more nearly, and enhances radar imagery effect, to realize that high resolution radar imaging has established model basis；It is and first
Radar imaging system is divided into sub-aperture or sub-band enters by secondary propose using three kinds of sparse characteristics of target generalized reflection rate
Row approximate calculation；It is proposed that imaging region is divided into a series of sub- imaging regions according to system function characteristic first, i.e., by one
Large scale electromagnetism inverse problem is converted into a series of small yardstick electromagnetism inverse problems, has greatly accelerated image taking speed；It is it is further proposed that sharp
Traditional radar imagery problem is converted into the image processing problem based on physical mechanism with dualistic transformation；The present invention both ensure that
Radar imagery precision accelerates radar imagery speed again, and large scale high resolution radar real time imagery can not be carried out by efficiently solving
Technical barrier.
Brief description of the drawings
Fig. 1 is the embodiment one and reality of the high resolution radar fast imaging method based on generalized reflection rate model of the present invention
Apply the structural representation of the Three-dimensional Simulation System of scene corresponding to example two；
Fig. 2 is the embodiment one according to the high resolution radar fast imaging method based on generalized reflection rate model of the present invention
Obtained imaging results figure, wherein, the number that figure (a)~(f) is respectively the sub- imaging region B divided is 1,3,9,27,63 and
127 imaging results figure；
Fig. 3 is the embodiment two according to the high resolution radar fast imaging method based on generalized reflection rate model of the present invention
Obtained imaging results figure, wherein, the number that figure (a)~(f) is respectively the sub- imaging region B divided is 1,4,8,12,24 and
32 imaging results figure.
Embodiment
Below in conjunction with the accompanying drawings, by specific embodiment, the present invention is expanded on further.
Embodiment one
In the present embodiment, the structure of Three-dimensional Simulation System is as shown in figure 1, radar imaging system uses the more of bistatic
Input multi-output antenna technology MIMO (Multiple-Input Multiple-Output) radar imaging system.
The high resolution radar fast imaging method based on generalized reflection rate model of the present embodiment, comprises the following steps：
1) radar imaging system is established, obtains radar scattering data：
Radar imaging system includes four emitters, 1~4,240 receivers, a width of 1~3Ghz of band of transmission signal, hair
Machine is penetrated to targeted imaging region transmission signal, it is after t-th of emitter transmission signal, then each by receiver receives echo-signal
Echo-signal at receiver is represented by yF,t=[yF,t,1；уF,t,2；…уF,t,R]；Four triangles in Fig. 1 represent 4
Emitter 1~4；In the round dot of same three-dimensional planar it is radar receiver with it, is respectively positioned on y=0 planes；Radar emission signal is adopted
With Gaussian modulation impulse wave；One three-dimensional cartoon personage target is located at the front of radar imaging system, and its dielectric constant is 50,
Head is made up of a diameter of 0.44m ball, and arms and legs are formed by a diameter of 0.1m cylinder, and cartoon figure is total
Highly it is about 1.8m.Other systems parameter is plotted on Fig. 1, and it is big that targeted imaging region is split into 0.1m × 0.1m × 0.1m
Small square volume mesh.
2) generalized reflection rate model is established：
Generalized reflection rate model is on the basis of traditional Born approximation model, it is included each to different of imageable target
Property characteristic, and the characteristics of different frequency range is to the action effect difference of imageable target, i.e. the transmitting letter of different angle different frequency
It is number different in induced-current caused by imageable target place.Four emitters then represent four sub-apertures herein.
3) data conversion and Data Integration：
A) because the echo-signal that receiver receives is time domain echo-signal, using Fast Fourier Transform (FFT) FFT by when
Domain echo-signal is transformed to frequency domain echo signal；
B) according to the Structural Characteristics of radar system function, according to generalized reflection rate model, radar imaging system is divided
For 4 sub-apertures, i.e. each emitter is a sub-aperture, is divided into targeted imaging region according to far-field effect method is ignored
Targeted imaging region is respectively divided into the sub- imaging area of B=1,3,9,27,63 and 127 by B sub- imaging regions, the present embodiment
Domain；According to above-mentioned division result, arrangement is combined to frequency domain echo signal, obtained on b-th of sub- imaging region and k-th
The echo data function y of sub-aperture(k,b), the system function of the dyadic Green's function construction radar imagery in free space
A(k,b), meet：
y(k,b)=A(k,b)x(k,b)+n(k,b)
Then radar imagery problem, which is converted into, solves unknown number x in equation (1)(k,b)Inverse problem, wherein, x(k,b)For broad sense
Reflectivity；
C) dualistic transformation：Matrix (A is multiplied by above formula both ends(k,b))*Obtain the system function B of image procossing(k,b)After and
To projection imaging result z(k,b)：
Traditional radar imagery problem is converted into the radar image process problem based on physical mechanism.
4) parallel imaging is carried out to sub- imaging region：Based on generalized reflection rate model, for equation (2) according to Gradient Iteration
Algorithm carries out parallel imaging to each sub- imaging region, the m times iteration of k-th of sub-aperture under its b-th sub- imaging region
Obtain generalized reflection rateMeet equation (3) i.e.：
Wherein,For the step of the m times iteration of k-th of sub-aperture under b-th of sub- imaging region
The long factor,For the m times of k-th of sub-aperture under b-th of sub- imaging region
The gradient function of iteration；
Using generalized reflection rate model, by the imaging results x of all K sub-apertures under b-th of sub- imaging region(k,b)(1
≤ k≤K, 1≤b≤B) image co-registration is carried out, obtain the imaging results x of b-th of sub- imaging region(b)(1≤b≤B).This implementation
Example is using (1,2) mixing norm, its process such as following formula：
Wherein, N represents x(k,b)Element number, n represents nth elements.
5) image co-registration：
The imaging results of B sub- imaging regions are carried out to the high score of the available width complete object imaging region of image co-registration
Radar imagery result is distinguished, the number of the sub- imaging region of division is different, respectively obtains different imaging effects, as shown in Figure 2.Draw
Divide the relation of the sub- imaging region of different numbers and the imaging time that is averaged as shown in table 1 below：
Table 1
From table 1 it follows that as the number of sub- imaging region increases, average imaging time, can with exponential reduction
To find out that the division of sub- imaging region greatly accelerates image taking speed.But as shown in Figure 2, increase with the number of sub- imaging region
More, also worse and worse, target is increasingly difficult to recognize imaging effect.Then it can be seen that image taking speed and imaging effect need to obtain
Effective compromise.But such as scheme it has also been discovered that imaging time is short but imaging effect good imaging results again from Fig. 2 and table 1
Middle c and d.
Embodiment two
In the present embodiment, according to the b of step 3)) in second seed imaging region division methods, i.e., adjacent first constant method will
Targeted imaging region is divided into B sub- imaging regions, the present embodiment by targeted imaging region be respectively divided into B=1,4,8,12,
24 and 32 sub- imaging regions.Other are the same as embodiment one.The number of the sub- imaging region of division is different, respectively obtain it is different into
Picture effect, as shown in Figure 3.
In the present embodiment, the relation for dividing the sub- imaging region and average imaging time of different numbers is as shown in table 2 below：
Table 2
From Table 2, it can be seen that embodiment two demonstrates the correctness of the conclusion of embodiment one：With of sub- imaging region
Number increases, and average imaging time is with exponential reduction, it can be seen that the division of sub- imaging region greatly accelerates image taking speed.But
From the figure 3, it may be seen that as the number of sub- imaging region increases, imaging effect also slightly deteriorates.Thus image taking speed and imaging effect
Need effectively to be compromised.But it has also been discovered that imaging time is short but imaging effect good imaging knot again from Fig. 3 and table 2
Fruit, such as c and d in figure.
It is finally noted that the purpose for publicizing and implementing example is that help further understands the present invention, but this area
Technical staff be appreciated that：Without departing from the spirit and scope of the invention and the appended claims, it is various to replace and repair
It is all possible for changing.Therefore, the present invention should not be limited to embodiment disclosure of that, and the scope of protection of present invention is to weigh
The scope that sharp claim defines is defined.
Claims (6)
- A kind of 1. high resolution radar fast imaging method based on generalized reflection rate model, it is characterised in that the imaging method Comprise the following steps：1) radar imaging system is established, obtains radar scattering data：Radar imaging system includes T emitter, and R receiver, the frequency number of transmission signal is F, and emitter is successively to mesh Imaging region transmission signal is marked, and by whole receiver receives echo-signals, then it is each after t-th of emitter transmission signal The echo-signal received at receiver is followed successively by yF,t=[yF,t,1；F,t,2；…F,t,R], wherein, T and R respectively >=2 nature Number, t=1,2 ..., T, F are >=2 natural number；2) generalized reflection rate model is established：Generalized reflection rate model is built upon on the basis of Born approximation model, and the anisotropic properties comprising imageable target and frequency The reflectivity of imageable target is different under rate characteristic, i.e. different angle emitter, the reflectivity of imageable target under different operating frequency Different characteristics；3) data conversion and Data Integration：A) receiver receives frequency domain echo signal；B) according to the Structural Characteristics of radar system function, according to generalized reflection rate model, radar imaging system is divided into K Sub-aperture or sub-band, and targeted imaging region is divided into B sub- imaging regions, according to above-mentioned division result, frequency domain is returned Ripple signal is combined arrangement, obtains the echo data function on b-th of sub- imaging region and k-th of sub-aperture or sub-band y(k,b), wherein, k=1,2 ..., K, b=1,2 ..., B, radar imaging system letter is constructed according to free space dyadic Green's function Number A(k,b), then generalized reflection rate x(k,b)Meet equation (1)：y(k,b)=A(k,b)x(k,b)+n(k,b) (1)Wherein, n(k,b)Model error is represented, then radar imagery problem, which is converted into, solves unknown number x in equation (1)(k,b)Inverse ask Topic；C) system function A is multiplied by respectively on equation (1) both sides(k, b)Associate matrixThe pairing of lines is entered to equation (1) Conversion obtains equation (2)：<mrow> <msub> <mi>z</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mo>=</mo> <msub> <mi>B</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <msub> <mi>x</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mo>+</mo> <msub> <mover> <mi>n</mi> <mo>~</mo> </mover> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>Wherein,It is the system function for representing image procossing,It is to represent backward Projection imaging result, n(k,b)It is model error, radar imagery problem is converted into the thunder based on physical mechanism by above-mentioned dualistic transformation Up to image processing problem；4) parallel imaging is carried out to sub- imaging region：Based on generalized reflection rate model, according to Gradient Iteration algorithm each sub- imaging region is carried out for equation (2) parallel into Picture, the m times iteration of k-th of sub-aperture or sub-band under b-th of sub- imaging region obtain generalized reflection rateSatisfaction side Journey (3)：<mrow> <msubsup> <mi>x</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> <mi>m</mi> </msubsup> <mo>=</mo> <msubsup> <mi>x</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>+</mo> <msubsup> <mi>&alpha;</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <msubsup> <mi>d</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>Wherein,Changed for k-th of sub-aperture under b-th of sub- imaging region or the m times of sub-band The step factor in generation,For k-th of sub-aperture under b-th of sub- imaging region Or the gradient function of the m times iteration of sub-band,For B(k,b)Associate matrix；Using generalized reflection rate model by the imaging results x of all K sub-apertures under b-th of sub- imaging region(k,b)Carry out figure As fusion, the imaging results x of b-th of sub- imaging region is obtained(b)：<mrow> <msub> <mi>x</mi> <mrow> <mo>(</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mo>=</mo> <mo>|</mo> <mo>|</mo> <msub> <mi>x</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mo>|</mo> <msub> <mo>|</mo> <mrow> <mi>p</mi> <mo>,</mo> <mi>q</mi> </mrow> </msub> <mo>=</mo> <msup> <mrow> <mo>(</mo> <msubsup> <mo>&Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </msubsup> <msup> <mrow> <mo>(</mo> <mrow> <msubsup> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </msubsup> <msup> <mrow> <mo>|</mo> <mrow> <msub> <mi>x</mi> <mrow> <mo>(</mo> <mi>k</mi> <mo>,</mo> <mi>b</mi> <mo>)</mo> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mo>|</mo> </mrow> <mi>p</mi> </msup> </mrow> <mo>)</mo> </mrow> <mrow> <mi>q</mi> <mo>/</mo> <mi>p</mi> </mrow> </msup> <mo>)</mo> </mrow> <mrow> <mn>1</mn> <mo>/</mo> <mi>q</mi> </mrow> </msup> <mo>,</mo> <mn>2</mn> <mo>&le;</mo> <mi>p</mi> <mo>&le;</mo> <mi>&infin;</mi> <mo>,</mo> <mn>0</mn> <mo>&le;</mo> <mi>q</mi> <mo>&le;</mo> <mn>1</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow>Wherein, N represents x(k,b)Element number, n represents nth elements, and n=1,2 ..., N, p and q are norm indexes；5) image co-registration：By the imaging results x of B sub- imaging regions(b)Carry out the high score that image co-registration can obtain a width complete object imaging region Distinguish radar imagery image X.
- 2. imaging method as claimed in claim 1, it is characterised in that step 3) a) in, if what receiver received Echo-signal is time domain echo-signal, then time domain echo-signal is transformed into frequency domain echo letter using Fast Fourier Transform (FFT) FFT Number.
- 3. imaging method as claimed in claim 1, it is characterised in that in the b of step 3)) in, sub- imaging region division includes Two kinds of different methods：I. far-field effect method is ignored：The characteristics of using correlation or weaker action effect between two distant elements, will Targeted imaging region is divided into the sub- imaging region of B imbricate, ignores the influence between distant element；Ii. adjacent first constant method：It is approximately a constant using the interaction between two adjacent elements, adjacent element is reflected Rate is set to identical value in same equation, i.e., original targeted imaging region is divided into B interlaced sub- imaging regions, The large scale multivariate linear equations of solution are approximately a series of multivariate linear equations of small yardsticks.
- 4. imaging method as claimed in claim 1, it is characterised in that in step 4), based on generalized reflection rate model, according to Gradient Iteration algorithm carries out distributed solution to equation (2), and carrying out the specific of parallel imaging to each sub- imaging region was imaged Journey is as follows：A) imaging results under each sub-aperture or sub-band are iterated to calculate：I. iteration the m times, the gradient function of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is calculatedIi. iteration the m times, the step factor of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is updatedIii. iteration the m times, the generalized reflection rate of k-th of the sub-aperture or sub-band under b-th of sub- imaging region is updatedIv. judge whether to meet iterated conditional, such as meet, then into step b), be such as unsatisfactory for, then return to step i)；B) by the imaging results x of the different sub-apertures of b-th of sub- imaging region(k,b)It is fused into piece image x(b)。
- 5. imaging method as claimed in claim 1, it is characterised in that in step 5), according to the side of sub- imaging region division Method, the method for determining image co-registration.
- 6. imaging method as claimed in claim 5, it is characterised in that ignore far field as fruit imaging region division methods use Effect method, then image co-registration use average weighted method；Such as the adjacent first constant method of fruit imaging region division methods use, then scheme As fusion is using the method for interpolation.
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